class_docstr: Implements a dataset folder.
  
  DatasetFolder based on torchvisions implementation.
  (https://pytorch.org/docs/stable/torchvision/datasets.html#datasetfolder)
  
  Attributes:
      root:
          Root directory path
      loader:
          Function that loads file at path
      extensions:
          Tuple of allowed extensions
      transform:
          Function that takes a PIL image and returns transformed version
      target_transform:
          As transform but for targets
      is_valid_file:
          Used to check corrupt files
  
  Raises:
      RuntimeError: If no supported files are found in root.
docstr: Returns the number of samples in the dataset.
docstr_tok: ["Returns","the","number","of","samples","in","the","dataset","."]
code: def __len__(self):
      """Returns the number of samples in the dataset."""
      return len(self.samples)
  
file_path: lightly/lightly/data/_image.py
imports: import os
  from typing import List, Set, Tuple
  import torchvision.datasets
  from torchvision import transforms
  from lightly.data._image_loaders import default_loader
label_desc: Use image node_id 3 for calling the DatasetFolder obj's underlying member method code with example usage: obj.__len__() and returns: len